Radiologists are faced with ever increasing workloads resulting from the ever increasing number of images to be analyzed, classified and described. Classifying image data may be useful, for example, for image data retrieval. Nowadays, a class of image data is typically based on the acquisition modality, e.g. CT, part of the anatomy represented by the image data, e.g. chest, gender and age group of the patient, e.g. male, young adult, and objects described by the image data. Description of the anatomy represented by the image data is particularly time consuming and often requires studying many images rendered based on acquired image data. The rendered images are viewed and described by radiologists. In order to assist a radiologist in his tasks, software implemented image analysis systems are available. Many software packages provide interactive tools for measuring objects in the image. For example, the user may select two points on the wall of a blood vessel for computing a distance between the two points, yielding the diameter of the vessel. Other systems include image segmentation systems for delineating features such as edges and surfaces in images and measuring tools for measuring objects in the image data on the basis of the image segmentation. For example, WO 2003/023717 entitled Automated Measurement of Geometrical Properties describes a method of measuring a geometric parameter of a three-dimensional structure contained in an object, using model-based image segmentation. First, a first model is adapted to an object in the image data. Then, a second model is fitted to the adapted first model by adjusting the value of the geometric parameter of the second model. For example, the second model may be a sphere and the geometric parameter may be the sphere diameter. The first model may be a triangular mesh for adapting to a femur bone depicted in the image data. The sphere may be fitted to the femur head. After obtaining necessary parameter values, the radiologist is required to describe the findings and/or classify the image data based on the findings. Typically this is done by dictating a description and using speech recognition techniques for converting speech to text.